A Forrester analysis of Bombora data shows an 18% conversion rate lift by prioritizing accounts with high-intent signals. This guide details the numbers.

A 2024 Forrester analysis of Bombora's Company Surge® data found that prioritizing accounts based on high-intent signals improved conversion rates by up to 18%. [11, 18] The methodology defines a qualified lead by a 'Surge' in research activity, which occurs when an account's content consumption on specific topics significantly exceeds its 12-week historical baseline. [19] This data, sourced from a cooperative of over 5,000 B2B websites, allows sales teams to focus on accounts that are actively in-market. [14]

TL;DR

Prioritizing leads with Bombora intent data can increase conversion rates by up to 18%, according to a Forrester Total Economic Impact study. [11, 18]
6sense's 2024 research shows 92% of B2B buying involves groups of 3 or more, making account-level intent signals critical. [8]
Bombora's Company Surge® data is sourced from a co-op of nearly 6,000 publisher websites tracking over 20,000 topics. [16]
ZoomInfo intent data faces challenges, with 52% of sales professionals reporting frequent false positives from sources like bidstream data. [1]
For local SMBs, where intent data has near-zero coverage, direct directory sourcing yields ~70% verified email deliverability on owner contacts.

What Is B2B Intent Data and How Does Bombora Measure It?

B2B intent data is the aggregated digital footprint that reveals which companies are actively researching products or services, allowing revenue teams to focus on accounts that are in-market. This information is gathered by tracking the online research behaviors of businesses across a vast network of websites, with industry leaders like Bombora analyzing billions of content consumption events monthly. [13] The process involves monitoring which articles are read, which whitepapers are downloaded, and which topics a company's employees are collectively studying. This digital body language, when aggregated at the company level, provides a powerful signal of purchasing intent long before a prospect fills out a contact form. According to a 2026 analysis from MarketBetter, this methodology is what allows sales and marketing teams to move beyond static, firmographic-based targeting and engage accounts that are demonstrating active interest right now. [22] This approach is critical in a landscape where a significant portion of the buyer's journey happens digitally and anonymously. By identifying these early research signals, companies can prioritize outreach and personalize messaging for accounts showing genuine, timely interest in a solution.

Bombora's Company Surge® platform measures this intent by using a massive, consent-based Data Cooperative, which as of 2024 includes over 5,500 B2B publisher websites. [15] This cooperative model is a key differentiator, as it relies on direct, privacy-compliant relationships with publishers who share anonymized reader behavior data. [16, 22] This network captures billions of monthly content consumption events, creating a comprehensive view of the B2B research landscape. [13] For each company being tracked, Bombora establishes a historical baseline of its normal content consumption patterns across more than 13,000 specific B2B topics. [22] This baseline is crucial, as it represents the typical, everyday research activity for that organization. The data collection is designed to be privacy-centric, focusing only on consented data and aggregating signals at the company level, not the individual, to comply with regulations like GDPR and CCPA. [18] This ethically sourced foundation allows Bombora to understand what is normal before it can identify what is exceptional.

A 'Surge' score is calculated when a company's research activity on a specific topic significantly spikes above its historical 12-week baseline, signaling a shift from passive interest to active buying consideration. [2, 14] According to Bombora's 2023 Market Insights User Guide, a score of 60 or higher indicates a statistically significant increase in content consumption, flagging the account as 'surging' on that topic. [5, 12] This score is not a simple volume metric; it is a composite calculation that considers factors like the number of unique users from the company researching the topic, the frequency of their interactions, and the depth of their engagement with the content. [5] Crucially, the entire methodology is built around privacy by tracking activity at a company level, often through corporate IP addresses and anonymized cookies, rather than identifying or tracking individuals. [17, 20] This ensures compliance with global privacy standards while still providing the actionable intelligence needed to identify companies that have entered an active buying cycle, allowing sales teams to engage with the right accounts at precisely the right time.

How Many Signals Correlate to Pipeline Conversion Rates?

A multi-year analysis highlights a direct correlation between the integration of third-party intent data and escalating pipeline conversion rates. A commissioned Total Economic Impact™ study conducted by Forrester Consulting revealed that a composite organization using Bombora's Company Surge® data saw conversion rates improve by 8% in the first year, 13% in the second, and a significant 18% by the third year. [8] This progressive improvement underscores the cumulative value of intent data; it is not a one-time fix but a strategic asset that yields increasing returns as teams refine their processes and deepen their understanding of buying signals. The methodology involved analyzing a composite organization's performance over three years, attributing the gains to the ability to prioritize accounts showing active demand. This sustained lift demonstrates that as sales and marketing teams become more adept at interpreting and acting on intent signals, their efficiency and effectiveness in converting leads into tangible pipeline grows substantially, moving beyond initial low-hanging fruit to systematically improving outreach and engagement. The study provides a framework for evaluating the financial impact, showing how identifying in-market buyers earlier leads directly to higher conversion. [8]

The precision of an intent signal is critical, and a 'Surge' score exceeding 60 on Bombora's 0-100 scale indicates a pivotal shift in an account's research behavior. This threshold signifies that a company's content consumption on a specific topic has statistically surpassed its own 12-week historical baseline, moving it from passive interest into an active evaluation or decision-making phase. [1, 5] According to Bombora's 2022 user guide, this score is calculated by analyzing multiple factors, including the number of users from a business researching a topic, the frequency of their interactions, and the depth of their engagement. [1] Marketing and sales teams use this score as a primary filter to identify accounts that are genuinely in-market. A score below 40 suggests a decrease in interest, while scores between 40 and 60 represent baseline activity. [1] By focusing resources on accounts with a Company Surge® score of 60 or higher, organizations can prioritize outreach effectively, ensuring they engage prospects at the exact moment they are most receptive to a solution, which is a core principle detailed in documents like the Bombora-Salesforce Technical Architecture Integration v7.3 February 2025. [4]

Combining first-party website data with third-party intent signals creates a multiplier effect on conversion rates, providing a more complete picture of an account's buying journey. Qualified, a Bombora-powered partner, reports that this synthesis of data results in a 4x increase in lead conversion and a 6x growth in pipeline. [3, 18] This performance lift is achieved by layering Bombora's broad, topic-based research signals over the specific, high-intent behaviors observed directly on a company's own website. For example, knowing an account is researching 'Cloud Security' (a third-party signal) becomes exponentially more valuable when a user from that same account visits your pricing page (a first-party signal). This combination allows for precise, timely, and highly personalized engagement. Furthermore, broader industry analysis supports this, with some marketing teams using intent data effectively seeing up to 70% higher conversion rates on specific campaigns. [20] This synergy overcomes the limitations of each data type; first-party data is accurate but limited to known visitors, while third-party data provides scale but can lack specific context. Together, they enable revenue teams to identify and engage sales-ready accounts that would otherwise remain invisible. [15, 28]

Vendor / Platform	Primary Data Source(s)	Key Differentiator	Reported Performance Metric	Annual Contract Starting Price (Approx.)
Bombora	Third-Party Data Co-op (5,000+ B2B sites)	Broadest third-party topic coverage (17,000+ topics) delivered as a signal feed.	Composite organization saw 18% conversion lift over 3 years. [8]	$25,000 - $40,000
6sense	First-Party (own site) + Third-Party (Bombora, G2, etc.)	Predictive AI model for buying stages and full ABM platform orchestration.	Used by clients to achieve outcomes like 27x ROI. [11]	$60,000 [12]
Demandbase	First-Party (own site) + Third-Party (proprietary network + Bombora)	Strongest for account-based advertising orchestration and native DSP.	Acquired Engagio/InsideView to build a comprehensive Account Intelligence Cloud. [27]	$50,000+
ZoomInfo	First-Party (WebSights) + Third-Party (Bidstream, content, review sites)	Combines massive contact database with streaming intent signals updated daily.	Users layering G2 data saw 17% higher conversion rates. [13]	$30,000 - $50,000
Qualified	First-Party (own site) + Third-Party (Bombora)	Conversational platform built for Salesforce; converts site visitors in real-time.	Reports a 4x increase in lead conversion when combining data types. [3, 18]	Custom (Platform + Usage)
G2 Buyer Intent	Second-Party (G2.com review site activity)	High-intent signals from buyers actively comparing vendors on a trusted review site.	Can deliver a 4x ROI on campaign spend. [13]	$10,000 - $25,000 [12]

How Do Platforms Like 6sense and ZoomInfo Operationalize Intent?

Platforms like 6sense operationalize intent by moving beyond individual lead scores to a holistic, account-level view of buying signals. The 6sense Revenue AI platform captures trillions of buyer signals from its proprietary network, first-party customer data, and third-party sources to identify not just single interested contacts, but entire buying groups showing purchase intent. Its AI-driven models analyze patterns in this data to predict which accounts are in-market and their stage in the buying journey, a process it calls creating 6sense Qualified Accounts (6QAs). This methodology focuses on uncovering anonymous research activity in what 6sense terms the 'Dark Funnel,' where prospects explore solutions before ever filling out a form. By using patented identity resolution and per-customer AI models, the platform aims to resolve disparate signals into clear intelligence, answering why a specific account is showing interest now and which decision-makers are involved. This allows revenue teams to shift from reacting to form fills to proactively engaging accounts that AI has identified as showing predictive buying behavior.

ZoomInfo layers multiple types of intent data to identify in-market accounts, but its methodology faces documented accuracy challenges. The platform aggregates signals from four main sources: tracking content consumption across the web, analyzing bidstream advertising data, using its WebSights product for IP-based website visitor identification, and integrating with third-party review sites. While this multi-source approach aims to create a comprehensive view, a 2025 analysis highlighted that 29% of sales professionals cite misattributed IP data as a primary challenge with the platform's intent features. This issue is exacerbated by the rise of remote work and VPN usage, which makes matching an IP address to a specific company increasingly unreliable. Furthermore, some critics note that its use of bidstream data, which captures ad clicks, can generate noise and false positives, as not every interaction with an ad signifies genuine purchase intent. To mitigate these issues, experts recommend cross-referencing ZoomInfo's signals with first-party engagement data from a CRM to validate interest and focus on stronger signals like pricing page visits over weaker ones like blog reads.

The B2B intent data market was clearly defined in The Forrester Wave™: B2B Intent Data Providers, Q1 2025, which named 6sense, Bombora, and Intentsify as market Leaders based on the strength of their current offerings and strategic vision. The report evaluated 15 top vendors on 21 criteria, recognizing Intentsify with the highest score in the 'Current Offering' category for its advanced capabilities in persona-based analysis and insight generation. 6sense was highlighted as a top-performing option for customers seeking strong analytics and a unified platform for both marketing and sales. Bombora, whose Company Surge® data is resold or integrated by numerous other platforms including 6sense and RollWorks, was recognized for its foundational role in the ecosystem, built on a cooperative of over 5,000 B2B publisher websites. Platforms like RollWorks operationalize this data by allowing customers to select from Bombora's intent topics to build and target audiences for account-based advertising campaigns.

Specialized platforms enable marketers to translate raw intent signals into targeted activation across advertising and sales channels. RollWorks, for example, directly integrates Bombora's Company Surge® data into its account-based platform, allowing users to select up to 100 intent topics to monitor. When an account shows a spike in research activity on these topics, it can be automatically added to a target list for digital advertising campaigns, ensuring ad spend is focused on accounts with active interest. Similarly, Intentsify differentiates itself by using natural language processing and large language models to create custom, solution-specific intent models based on a client's own marketing materials and positioning. This approach moves beyond predefined topics to identify prospects researching the specific value propositions that define a product. According to a February 2023 announcement, this 'precision intent' methodology gives users visibility down to the URL level, providing greater confidence in signal validity. Intentsify then activates these highly specific, persona-level insights through managed services for programmatic advertising and content syndication. This demonstrates a critical trend: the value of intent data is realized not just in its collection, but in its direct application to go-to-market execution.

Platform	Primary Intent Source	Key Feature/Methodology	Noted Limitation or Focus	Forrester Wave (Q1 2025) Position
6sense	Proprietary signal network ('Signalverse'), first-party data, third-party integrations (e.g., G2, Bombora).	Uses AI and predictive modeling to identify entire buying groups and qualify accounts (6QAs) based on predicted buying stage.	Enterprise-focused platform with pricing that can be prohibitive for smaller teams, starting around $60K+/year.	Leader
ZoomInfo	Content consumption, bidstream data, IP-based web tracking (WebSights), and review site partnerships.	Combines a massive contact database with multiple intent signal types to provide a broad view of account activity.	Users report issues with data accuracy, particularly IP misattribution (cited by 29% of users) and false positives from bidstream data.	Leader
Bombora	Proprietary data cooperative of over 5,000 B2B websites.	Company Surge® score measures when an account's content consumption on a topic spikes above its historical baseline.	Primarily provides account-level topic data; does not identify individual contacts or offer built-in activation tools itself.	Leader
Intentsify	Monitors over 1.1 trillion monthly signals from third-party sources.	Builds custom, solution-specific intent models using NLP to align signals with a client's unique products and messaging.	Operates on a managed service model, which may not suit teams wanting direct platform control.	Leader
RollWorks	Integrates Bombora's Company Surge® data as its primary third-party intent source.	Natively embeds intent data for building target account lists and activating ABM digital advertising campaigns.	Intent data is primarily for use within the RollWorks platform for ad targeting and cannot be exported for other uses.	Not Rated (Considered an ABM Platform)
Anteriad	Multi-source intent data combined with demand generation services.	Offers a full-funnel solution combining an intelligence layer with an execution layer for campaigns.	Focus is on providing marketing services, which may be more than teams needing only a data feed require.	Strong Performer

The SMB Data Gap: Why Intent Signals Fail for Local Businesses

Intent data co-ops fundamentally fail to track small and local businesses because their core methodology relies on identifiable corporate IP blocks. Platforms like Bombora build their datasets, including the popular Company Surge® product, from a cooperative of over 5,000 B2B websites that share anonymized visitor data. The system works by mapping content consumption, such as billions of monthly interactions, back to a specific company's IP address, a process Bombora calls its Business Identity Mapping. This model is effective for enterprise and mid-market companies with dedicated, registered IP blocks that clearly identify their corporate network. However, it creates a massive data gap for local businesses like salons, plumbers, or independent consultants. These small business owners conduct research from their homes or small offices using residential internet service providers like Comcast or Verizon. Their activity is anonymized and mixed with general consumer traffic, rendering them invisible to IP-to-company mapping technologies and leaving them with near-zero representation in these sophisticated B2B intent datasets.

Major B2B data providers like ZoomInfo and Apollo.io offer minimal coverage for the smallest businesses, making them unreliable for prospecting local service companies. While platforms like ZoomInfo boast databases of over 100 million company profiles, their focus and pricing models are explicitly designed for mid-market and enterprise clients. A 2026 analysis noted that ZoomInfo's starting price of nearly $15,000 per year is often prohibitive for small businesses, and its complex features can overwhelm smaller teams. Similarly, Apollo.io, which provides access to roughly 275 million contacts, has its strongest coverage in the US market for tech-enabled companies, not main-street businesses. Reviews from 2026 highlight that while Apollo is a strong fit for small teams of under 10 reps doing email-based outbound, its data thins out considerably for niche or non-tech small businesses. This structural focus on larger, easier-to-identify companies means that verifiable data for named decision-makers at businesses with fewer than 10 employees is exceptionally scarce, with some analyses suggesting most companies access less than 10% of the available data due to the sheer volume and lack of relevance for smaller targets.

For local lead generation, sourcing contact information from public business directories provides a far more effective and verifiable alternative to intent data systems. While intent platforms struggle with SMB identification, public and local business directories serve as a foundational layer for local discovery and are trusted by search engines. These directories, ranging from Google Business Profile to industry-specific listings, contain self-reported and publicly verifiable information like owner names, phone numbers, and physical addresses. This approach directly addresses the data gap left by major providers. According to a 2026 report on local lead generation from GigaBPO, hyperlocal email campaigns can achieve conversion rates as high as 21%, significantly outperforming many paid channels. Furthermore, while general email marketing deliverability averages around 87% in North America, campaigns built from clean, permission-based local lists often see higher engagement and success. A 2025 analysis by LanderLab found that SMS campaigns to local lists can achieve a 98% open rate, demonstrating the power of direct, locally-sourced contact information for achieving near-perfect connection rates.

Building a Practical Lead Qualification Model with Factual Data

A practical lead qualification model must be anchored in verifiable, factual data, not the opaque scores characteristic of AI-slop. The foundational layer of any qualified lead is accurate contact information; a working email and phone number are non-negotiable prerequisites before any scoring or enrichment occurs. The cost of ignoring this principle is substantial, as poor data quality costs organizations an average of $12.9 million annually. B2B contact data decays at a rate of 2.1% per month, or 22.5% annually, meaning a significant portion of a CRM can become useless within a year. Sales teams using AI-only lead generation report that while volume may increase, the lack of human verification or grounding in factual data often leads to lower quality and wasted effort on leads that are fundamentally inaccurate. A model that prioritizes a verifiable email and phone number over ambiguous AI-generated "fit scores" ensures that sales development efforts are directed at real, reachable prospects, forming a solid base for all subsequent qualification steps.

The most cost-effective B2B lead qualification process establishes a baseline of low-cost, verifiable contact information before layering on more expensive intent data. This tiered approach prevents teams from wasting budget enriching contacts that are undeliverable or outdated. According to a 2026 pricing guide, B2B contact data costs can range from under $0.10 to over $1.50 per contact, making it critical to validate the basics first. Once a lead's contact information is confirmed, intent data from a provider like Bombora can be applied as a secondary enrichment step. This ensures that the significant investment in intent data, with some Bombora Company Surge® packages starting around $25,000 per year, is focused only on accounts that are confirmed to be reachable. This methodology, which separates the initial verification of contact data from the subsequent analysis of buying intent, creates a more efficient and financially sound qualification funnel. It avoids the common pitfall of paying premium prices to analyze intent signals for contacts that sales teams can't even reach, a problem that plagues teams relying on stale database records.

Instead of engineering complex, multi-factor scoring models, a simple threshold based on high-intent signals provides a clear, actionable trigger for sales development. Bombora's Company Surge® methodology defines this trigger with a score of 60 or higher, which indicates an organization is demonstrating a statistically significant increase in research on a specific topic compared to its own 12-week historical baseline. This score, which ranges from 0 to 100, is a direct measure of active demand, signaling that an account is in "buying mode" and should be prioritized by sales. A 2022 Forrester analysis of a Bombora customer found that implementing this prioritization strategy improved conversion rates by up to 18% over three years. By routing any account that crosses this simple, data-backed threshold directly to sales development, teams can act quickly on validated interest without the ambiguity of blended scores that mix firmographics, fit, and intent into a single, less transparent number. This approach was central to one organization's ability to see a 15% growth in revenue through increased conversion and sales velocity.

A fair billing model that includes per-lead bounce credits is a critical, though often overlooked, component of a practical data strategy, as it aligns incentives between the data buyer and vendor. Such a model contractually ensures you only pay for data that is verifiably deliverable and accurate. When a data provider offers a 95%+ accuracy guarantee with bounce replacement, it directly addresses the high cost of bad data, where bounce rates above 5% can damage a company's sender reputation and risk domain blacklisting. This stands in contrast to pricing models where credits are consumed regardless of whether an email bounces, forcing the buyer to absorb the cost of outdated information. A service-level agreement (SLA) that formalizes data quality metrics like accuracy and timeliness serves as an enforceable contract for this purpose. By demanding bounce credits, companies enforce a standard of quality and shift the financial risk of data decay, which can be as high as 22.5% annually, back onto the provider. This ensures that the budget allocated for lead acquisition is spent on tangible, reachable opportunities, not on cleaning a vendor's stale database.

Frequently Asked Questions

What is a good Bombora Surge score?

A Bombora Company Surge® score of 60 or higher is considered a strong signal that qualifies an account. [3, 6, 10] This score, on a scale of 0-100, indicates a statistically significant increase in an account's content consumption on a specific topic compared to its historical baseline. [10, 18] Scores between 40 and 60 represent normal activity, while scores below 40 show a decrease in research. [3] For the strongest intent signal, Bombora's best practices recommend combining a score of at least 60 with a topic threshold, which requires an account to surge on a minimum number of related topics. [6]

How much does B2B intent data cost?

The cost of B2B intent data varies widely, from free tiers to over $150,000 annually, depending on the provider and features. [2] Standalone intent data from a provider like Bombora typically starts around $25,000 to $30,000 per year, with median contracts near $24,750. [15, 19] All-in-one platforms that bundle intent data with contact databases, such as ZoomInfo, often price intent as an add-on costing between $7,200 and $40,000 annually. [1, 19] Enterprise ABM platforms like 6sense or Demandbase, which include predictive scoring and activation, represent the highest tier, often costing $60,000 to over $300,000 per year. [2, 15]

What is the difference between Bombora and ZoomInfo intent data?

The primary difference is their core function and data source methodology. Bombora is a specialized intent data provider that uses a cooperative of over 5,000 publisher websites to generate its account-level Company Surge® scores. [15, 25] In contrast, ZoomInfo is an all-in-one platform that combines its own proprietary intent signals with contact data, offering a single tool for both identifying and engaging leads. [1, 20] While Bombora offers a much larger taxonomy of over 17,000 topics, it only provides company-level signals, whereas ZoomInfo bundles intent with over 300 million contact profiles, though its topic count is smaller. [1]

Can you get intent data for small businesses?

Yes, several platforms offer intent data solutions suitable for small businesses, though enterprise tools are often too expensive. All-in-one platforms like Apollo.io and Cognism are often recommended for smaller teams because they bundle Bombora-powered intent signals with contact data at a lower price point. [16] Apollo offers a free tier and paid plans starting under $1,500 per year, making it an accessible entry point. [2, 19] These tools provide actionable intent without the high cost and operational overhead of enterprise ABM platforms, which often require dedicated staff to manage effectively. [16]

How is intent data used in account-based marketing (ABM)?

Intent data is foundational to modern account-based marketing (ABM) because it identifies which target accounts are actively researching relevant solutions. [7, 8] This allows marketing and sales teams to prioritize high-value accounts that are showing buying signals, rather than relying on static ideal customer profiles. [11] Practically, teams use these signals to trigger timely and personalized outreach, such as tailoring ad copy to the specific topics an account is researching or aligning sales follow-ups with their digital behavior. [5, 8] This data-driven approach ensures marketing budgets are focused on accounts more likely to convert, improving ROI and aligning sales and marketing efforts. [7]

Last updated: July 2026

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